1. Field of the Invention
The present disclosure generally relates to techniques that enable estimation of the so-called Doppler spread in mobile radio telecommunication systems and has been developed with particular but not exclusive attention paid to a possible application thereof to channel estimation in digital telecommunication systems exposed to fading phenomena. Reference to this specific field of application is not in any case to be understood as in any way limiting the scope of the invention, which is altogether general.
2. Description of the Related Art
Transmission systems, such as digital-transmission systems, operate with non-ideal transmission channels.
For example, in mobile radio systems the transmission channel has characteristics that vary according to the relative speed of the transmitter and the receiver. Consequently, there is a Doppler shift of the signals that propagate along the transmission channel according to the line of sight and, in the case of multiple paths, a phenomenon of Doppler spread. The latter phenomenon, in practically, takes the form of a smearing of the signal bandwidth along the frequency axis which is proportional to the speed. The situation is rendered even more critical by the fact that the fading phenomena have a selective behavior in frequency. However, there exists the possibility, using advanced modulation and demodulation techniques, of equating this phenomenon to the sum of fading phenomena that have a uniform behavior in frequency.
Techniques that achieve this result are, for example, spread-spectrum techniques in particular in conjunction with the receivers commonly referred to as “rake” receivers; this is, for example, the case of transmission systems that use the so-called code-division multiple access (CDMA) technique, which is adopted in third-generation mobile-phone systems, or else orthogonal frequency-division multiplexing (OFDM) techniques.
The impulse response of a channel affected by flat-type fading (i.e., non-selective in frequency) may be expressed in the form of a complex gain that can be modeled as a random process with a certain bandwidth, referred to as Doppler spread, which is proportional to the relative speed of the transmitter and the receiver. The shape of the power spectral density of the process depends upon the scattering environment and can be modeled according to different criteria, well known to persons skilled in the art.
Techniques aimed at compensating the non-ideal character of the channel can be basically reduced to two fundamental categories.
In the first place, there exist non-coherent detection techniques which, in order to avoid having to estimate the channel, resort to a modulation of a differential type.
There then exist coherent detection techniques, which compensate for channel distortion after having estimated the transfer function (or the impulse response) of the channel itself.
For this purpose, a technique commonly used for performing channel estimation is that of transmitting symbols known to the receiver, called pilot symbols. These signals are transmitted in a continuous way or, at least, with a rate sufficient to be able to follow the variations of the channel in all the operating conditions. Usually, the channel transfer function varies according to the relative speed of the transmitter and the receiver, and the characteristics of the pilot signals are defined in such a way as to be able to face up to the maximum expected speed.
Again, the use of pilot symbols can be adapted to the instantaneous operating conditions: for example, the number of pilot symbols to be used for instantaneous channel estimation can be chosen according to the effective speed. In effect, whenever the speed is less than the maximum expected speed, the pilot symbols may be redundant and can thus be exploited for increasing the reliability of channel estimation. For this reason, to test channel estimation it is advantageous to provide an estimation of the speed (or an estimation of Doppler spread—which is equivalent).
There exist different methods of channel estimation of an adaptive type driven by the statistics of the channel. For example, without thereby wishing in any way to exhaust the entire range of the literature on the subject, which is extremely vast, reference may be made to the work of H. Andoh et al.: “Channel Estimation Filter Using Time Multiplexed Pilot Channel for Coherent RAKE Combining in DS-CDMA Mobile Radio”, IEICE TRANS. COMMUN., vol. E81-B, n.7, July 1998, pp. 1517-1526, or to the patent documents US2002 167913, WO-A-02/063814, or U.S. Pat. No. 5,513,221.
In actual fact, knowledge of the Doppler spread provides useful information on the speed of a mobile terminal so that the corresponding information is useful not just for the purposes of the channel estimation but also for other operations such as, for example:                hand-off procedures, in so far as the measurements performed for enabling hand-off are more reliable if they take into account the speed of the mobile terminal, in particular adapting the measurement time window according to the speed of the mobile terminal, as illustrated for example in the work of M. D. Austin et al.: “Velocity Adaptive Hand-off Algorithms for Microcellular Systems”, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, vol. 43, n. 3, August 1994, pp. 549-561; and        cell assignment in hierarchical cellular systems, which requires the knowledge of the speed of the mobile terminal to determine whether to assign the user to cells of a micro or macro type, as described in the work of C. Xiao et al.: “Mobile Speed Estimation for TDMA-Based Hierarchical Cellular Systems”, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, vol. 50, n. 4, July 2001, pp. 981-991.        
Yet again as regards estimation of Doppler spread (which is the main statistical property for driving the channel-estimation function) a large number of different techniques have already been proposed, which envisage for example:                measurement of the crossing rate of a certain level (level-crossing rate or LCR), with the particular case of zero-crossing rate (ZCR)—treated in the article by Austin et al., already cited previously;        use of the autocovariance (see, for example, the work of M. Kirsch et al.: “Mobile Speed Estimation for 3G Mobile Radio Systems using the Normalized Autocovariance Function”—2002 International Zurich Seminar on the Broadband Communications Success—Transmission Networking, February 19-31, ETH Zurich, Switzerland (pp. 48-1-48-4);        recourse to the eigenspace method, documented in the work of M. D. Austin et al.,: “Eigen-Based Doppler Estimation for Differentially Coherent CPM”, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, vol. 43, n. 3, August 1994, pp. 781-785;        evaluation of the square deviations of the envelope compressed according to a logarithmic law, as described in the work of J. M. Holtzman et al.: “Adaptive Averaging Methodology for Handoffs in Cellular Systems”, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, vol. 44, n. 1, February 1995, pp. 59-66; and again        application of the continuous wavelet transform, as described in the work of R. Narasimhan et al.: “Speed Estimation in Wireless Systems Using Wavelets” IEEE International Conference on Communications: Jun. 6-10, 1999, Vancouver, British Columbia, Canada, pages 1773-1778.        
The zero-crossing method (ZCR) is usually applied to the envelope of the signal. Instead, in the documents US2002 167913 and WO-A-02/063814 already cited previously, the Doppler spread is estimated starting from the channel-gain estimation, using however an autocovariance-based method.